{"id":"https://openalex.org/W4228999603","doi":"https://doi.org/10.48550/arxiv.2205.01306","title":"CANShield: Deep Learning-Based Intrusion Detection Framework for Controller Area Networks at the Signal-Level","display_name":"CANShield: Deep Learning-Based Intrusion Detection Framework for Controller Area Networks at the Signal-Level","publication_year":2022,"publication_date":"2022-05-03","ids":{"openalex":"https://openalex.org/W4228999603","doi":"https://doi.org/10.48550/arxiv.2205.01306"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2205.01306","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2205.01306","pdf_url":"https://arxiv.org/pdf/2205.01306","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2205.01306","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5045241299","display_name":"Md Hasan Shahriar","orcid":"https://orcid.org/0000-0003-0289-8611"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Shahriar, Md Hasan","raw_affiliation_strings":["Virginia Polytechnic Institute and State University"],"affiliations":[{"raw_affiliation_string":"Virginia Polytechnic Institute and State University","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046618429","display_name":"Yang Xiao","orcid":"https://orcid.org/0000-0001-8549-6794"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiao, Yang","raw_affiliation_strings":["Virginia Polytechnic Institute and State University"],"affiliations":[{"raw_affiliation_string":"Virginia Polytechnic Institute and State University","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064588051","display_name":"Pablo Moriano Salazar","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Moriano, Pablo","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001879281","display_name":"Wenjing Lou","orcid":"https://orcid.org/0000-0002-2421-4623"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lou, Wenjing","raw_affiliation_strings":["Virginia Polytechnic Institute and State University"],"affiliations":[{"raw_affiliation_string":"Virginia Polytechnic Institute and State University","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113999511","display_name":"Thomas Y. Hou","orcid":null},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hou, Y. Thomas","raw_affiliation_strings":["Virginia Polytechnic Institute and State University"],"affiliations":[{"raw_affiliation_string":"Virginia Polytechnic Institute and State University","institution_ids":["https://openalex.org/I859038795"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5045241299"],"corresponding_institution_ids":["https://openalex.org/I859038795"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10761","display_name":"Vehicular Ad Hoc Networks (VANETs)","score":0.9728999733924866,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10761","display_name":"Vehicular Ad Hoc Networks (VANETs)","score":0.9728999733924866,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9456999897956848,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.7894184589385986},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7841810584068298},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.594895601272583},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5618172883987427},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.5389654636383057},{"id":"https://openalex.org/keywords/payload","display_name":"Payload (computing)","score":0.5369014739990234},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5117344856262207},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4875718951225281},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.48030585050582886},{"id":"https://openalex.org/keywords/controller","display_name":"Controller (irrigation)","score":0.4627878963947296},{"id":"https://openalex.org/keywords/data-pre-processing","display_name":"Data pre-processing","score":0.4502696990966797},{"id":"https://openalex.org/keywords/anomaly-based-intrusion-detection-system","display_name":"Anomaly-based intrusion detection system","score":0.42868250608444214},{"id":"https://openalex.org/keywords/data-stream","display_name":"Data stream","score":0.4243742525577545},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4103221893310547},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3535890579223633},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.20241564512252808}],"concepts":[{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.7894184589385986},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7841810584068298},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.594895601272583},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5618172883987427},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.5389654636383057},{"id":"https://openalex.org/C134066672","wikidata":"https://www.wikidata.org/wiki/Q1424639","display_name":"Payload (computing)","level":3,"score":0.5369014739990234},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5117344856262207},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4875718951225281},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.48030585050582886},{"id":"https://openalex.org/C203479927","wikidata":"https://www.wikidata.org/wiki/Q5165939","display_name":"Controller (irrigation)","level":2,"score":0.4627878963947296},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.4502696990966797},{"id":"https://openalex.org/C137524506","wikidata":"https://www.wikidata.org/wiki/Q2247688","display_name":"Anomaly-based intrusion detection system","level":3,"score":0.42868250608444214},{"id":"https://openalex.org/C2778484313","wikidata":"https://www.wikidata.org/wiki/Q1172540","display_name":"Data stream","level":2,"score":0.4243742525577545},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4103221893310547},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3535890579223633},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.20241564512252808},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C158379750","wikidata":"https://www.wikidata.org/wiki/Q214111","display_name":"Network packet","level":2,"score":0.0},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:oai:arXiv.org:2205.01306","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2205.01306","pdf_url":"https://arxiv.org/pdf/2205.01306","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:osti.gov:1873824","is_oa":true,"landing_page_url":"https://www.osti.gov/biblio/1873824","pdf_url":"https://www.osti.gov/servlets/purl/1873824","source":{"id":"https://openalex.org/S4306402487","display_name":"OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I139351228","host_organization_name":"Office of Scientific and Technical Information","host_organization_lineage":["https://openalex.org/I139351228"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null},{"id":"doi:10.48550/arxiv.2205.01306","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2205.01306","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2205.01306","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2205.01306","pdf_url":"https://arxiv.org/pdf/2205.01306","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5438776802","display_name":null,"funder_award_id":"CNS-1837519","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6559340904","display_name":"CPS: Medium: S2Guard: Building Security and Safety in Autonomous Vehicles via Multi-Layer Protection","funder_award_id":"1837519","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G848032724","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320306084","display_name":"U.S. Department of Energy","ror":"https://ror.org/01bj3aw27"},{"id":"https://openalex.org/F4320306250","display_name":"Battelle","ror":"https://ror.org/01h5tnr73"},{"id":"https://openalex.org/F4320316892","display_name":"UT-Battelle","ror":"https://ror.org/04nza6677"},{"id":"https://openalex.org/F4320338287","display_name":"Oak Ridge National Laboratory","ror":"https://ror.org/01qz5mb56"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2159052453","https://openalex.org/W3094337645","https://openalex.org/W2990799928","https://openalex.org/W2347501756","https://openalex.org/W2697709536","https://openalex.org/W2384998121","https://openalex.org/W3013472303","https://openalex.org/W2031030051","https://openalex.org/W2348816240"],"abstract_inverted_index":{"Modern":[0],"vehicles":[1],"rely":[2],"on":[3,106,220],"a":[4,136,152,175,179,196],"fleet":[5],"of":[6,25,35,59,90,109,149,184,233],"electronic":[7],"control":[8],"units":[9],"(ECUs)":[10],"connected":[11],"through":[12],"controller":[13],"area":[14],"network":[15],"(CAN)":[16],"buses":[17],"for":[18,143,174],"critical":[19],"vehicular":[20],"control.":[21],"With":[22],"the":[23,32,39,55,60,81,88,91,100,107,115,144,158,164,192,215,228],"expansion":[24],"advanced":[26,74,237],"connectivity":[27],"features":[28],"in":[29,123,235],"automobiles":[30],"and":[31,47,119,167,200,202,231],"elevated":[33],"risks":[34],"internal":[36],"system":[37],"exposure,":[38],"CAN":[40,61,92,110,145,160,224],"bus":[41],"is":[42],"increasingly":[43],"prone":[44],"to":[45,80,128,213],"intrusions":[46],"injection":[48,52],"attacks.":[49,126,239],"As":[50],"ordinary":[51],"attacks":[53],"disrupt":[54],"typical":[56],"timing":[57],"properties":[58],"data":[62,79,118,153,161,180,194],"stream,":[63],"rule-based":[64,95],"intrusion":[65,140,238],"detection":[66,141,206],"systems":[67],"(IDS)":[68],"can":[69,76],"easily":[70],"detect":[71,129],"them.":[72],"However,":[73],"attackers":[75],"inject":[77],"false":[78],"signal/semantic":[82],"level,":[83],"while":[84],"looking":[85],"innocuous":[86],"by":[87],"pattern/frequency":[89],"messages.":[93],"The":[94],"IDS,":[96,102],"as":[97,99],"well":[98],"anomaly-based":[101],"are":[103,120],"built":[104],"merely":[105],"sequence":[108],"messages":[111],"IDs":[112],"or":[113],"just":[114],"binary":[116],"payload":[117],"less":[121],"effective":[122],"detecting":[124,236],"such":[125,130],"Therefore,":[127],"intelligent":[131],"attacks,":[132],"we":[133],"propose":[134],"CANShield,":[135],"deep":[137,176,186],"learning-based":[138],"signal-level":[139],"framework":[142],"bus.":[146],"CANShield":[147,234],"consists":[148],"three":[150],"modules:":[151],"preprocessing":[154],"module":[155,182,207],"that":[156,208],"handles":[157],"high-dimensional":[159],"stream":[162],"at":[163],"signal":[165],"level":[166],"parses":[168],"them":[169],"into":[170],"time":[171],"series":[172],"suitable":[173],"learning":[177],"model;":[178],"analyzer":[181],"consisting":[183],"multiple":[185],"autoencoder":[187],"(AE)":[188],"networks,":[189],"each":[190],"analyzing":[191],"time-series":[193],"from":[195],"different":[197],"temporal":[198],"scale":[199],"granularity,":[201],"finally":[203],"an":[204,210],"attack":[205,225],"uses":[209],"ensemble":[211],"method":[212],"make":[214],"final":[216],"decision.":[217],"Evaluation":[218],"results":[219],"two":[221],"high-fidelity":[222],"signal-based":[223],"datasets":[226],"show":[227],"high":[229],"accuracy":[230],"responsiveness":[232]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
